Google BigQuery is a serverless data warehouse that performs scalable analysis over petabytes of data. Use a Google BigQuery catalog source to collect metadata from the assets in a Google BigQuery source system.
Objects extracted
Metadata Command Center extracts the following metadata from a Google BigQuery source system:
•Database
•Schema
•Table
•External Table
•Column
•View
•View Column
•Materialized View
Note: Objects of the Materialized View type appear as View in Data Governance and Catalog.
•Stored procedure
•SQL User-defined functions (UDF)
Note: Each time Metadata Command Center runs a scan on a Google BigQuery catalog source, Data Governance and Catalog displays the extracted objects along with the objects from the previous scans. This means that if you modify the filters in Metadata Command Center and run a scan, Data Governance and Catalog does not replace the objects from the previous scan. Instead, Data Governance and Catalog adds the newly extracted objects to the existing scanned objects. To see the results of only the latest scan, choose Delete as the Metadata Change Option before you run the scan.
Data profiling for Google BigQuery objects
Configure data profiling to run profiles on the metadata extracted from a Google BigQuery source system. You can run data profiles on the following objects:
•Table
•External Table
Note: You can run data profiles only on external tables that are created in Google Cloud Storage.
•Partitioned Table
•Views
•Materialized Views
The data profiling task runs profiles on the following data types:
•BOOLEAN
•DATE
•DATETIME
•FLOAT
•INTEGER
•NUMERIC
•STRING
•TIME
•TIMESTAMP
Data Lineage
The following lineage data is available for Google BigQuery assets:
•From table to view
For more information about data lineage, see Data Lineage in the Working With Assets help.